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Adaptively Scheduled Multitask Learning: The Case of Low Resource Neural Machine Translation

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Figure

Figure 1: The dynamic in the relative importance ofnamed entity recognition, syntactic parsing, and se-The plot shows our proposed adaptive scheduling vsfixed scheduling (mantic parsing as the auxiliary tasks for the main ma-chine translation task (based on our experiments in §3).Kiperwasser and Ballesteros, 2018)(scaled down for better illustration).
Figure 2: High-level idea for training an MTL architec-ture using adaptive importance weights (AIWs)
Figure 3: Computation graph of the proposed method for adaptively determining weights.
Table 1: Results for three language pairs. ”+ AIW” indicates Adaptive Importance Weighting is used in training.†: Proposed in (Zaremoodi and Haffari, 2018), ‡: Proposed in (Kiperwasser and Ballesteros, 2018).
+3

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